What are the hardware requirements for GLM 5.1 AWQ?

GLM 5.1 AWQ requires approximately 119.9 GB of VRAM and supports a context window of 198K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 5.1 AWQ and how large is it?

GLM 5.1 AWQ is developed by QuantTrio, a model with 753.9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate GLM 5.1 AWQ?

GLM 5.1 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.1 AWQ by QuantTrio — VRAM 119.9GB, 198K context

Name: GLM 5.1 AWQ
Author: QuantTrio

GLM 5.1 AWQ is an open-source language model by QuantTrio. Features: 753.9b LLM, VRAM: 119.9GB, Context: 198K, License: mit, MoE, Quantized, LLM Explorer Score: 0.29.

Arxiv:2602.15763 4-bit Awq Conversational Endpoints compatible Glm moe dsa Moe Quantized Region:us Safetensors Sharded Tensorflow Vllm

Model Card on HF 🤗: https://huggingface.co/QuantTrio/GLM-5.1-AWQ

GLM 5.1 AWQ Parameters and Internals

LLM Name	GLM 5.1 AWQ
Repository 🤗	https://huggingface.co/QuantTrio/GLM-5.1-AWQ
Base Model(s)	ZhipuAI/GLM-5.1 ZhipuAI/GLM-5.1
Model Size	753.9b
Required VRAM	119.9 GB
Updated	2026-08-08
Maintainer	QuantTrio
Model Type	glm_moe_dsa
Model Files	3.0 GB: 1-of-141 3.0 GB: 2-of-141 3.0 GB: 3-of-141 3.0 GB: 4-of-141 3.0 GB: 5-of-141 3.0 GB: 6-of-141 3.0 GB: 7-of-141 2.9 GB: 8-of-141 3.0 GB: 9-of-141 3.0 GB: 10-of-141 3.0 GB: 11-of-141 3.0 GB: 12-of-141 3.0 GB: 13-of-141 3.0 GB: 14-of-141 3.0 GB: 15-of-141 3.0 GB: 16-of-141 3.0 GB: 17-of-141 3.0 GB: 18-of-141 3.0 GB: 19-of-141 3.0 GB: 20-of-141 3.0 GB: 21-of-141 3.0 GB: 22-of-141 3.0 GB: 23-of-141 3.0 GB: 24-of-141 3.0 GB: 25-of-141 3.0 GB: 26-of-141 3.0 GB: 27-of-141 3.0 GB: 28-of-141 3.0 GB: 29-of-141 3.0 GB: 30-of-141 3.0 GB: 31-of-141 3.0 GB: 32-of-141 3.0 GB: 33-of-141 3.0 GB: 34-of-141 3.0 GB: 35-of-141 3.0 GB: 36-of-141 3.0 GB: 37-of-141 3.0 GB: 38-of-141 3.0 GB: 39-of-141 3.0 GB: 40-of-141
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	GlmMoeDsaForCausalLM
License	mit
Context Length	202752
Model Max Length	202752
Transformers Version	5.4.0
Vocabulary Size	154880

Rank the GLM 5.1 AWQ capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to GLM 5.1 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.1	198K / 231.9 GB	93343	1829
GLM 5	198K / 237.3 GB	156294	2119
GLM 5 FP8	198K / 243 GB	961083	182
GLM 5.1 FP8	198K / 237.6 GB	470901	119
GLM 5.1 Abliterated	198K / 226.8 GB	165	11
GLM 5.1 FP8	198K / 243 GB	30	5
GLM 5	198K / 242.7 GB	27	17

Note: green Score (e.g. "73.2") means that the model is better than QuantTrio/GLM-5.1-AWQ.